Risk factors for medication non-adherence among atrial fibrillation patients.

BACKGROUND: Atrial fibrillation (AF) patients are routinely prescribed medications to prevent and treat complications, including those from common co-occurring comorbidities. However, adherence to such medications may be suboptimal. Therefore, we sought to identify risk factors for general medication non-adherence in a population of patients with atrial fibrillation. METHODS: Data were collected from a large, ethnically-diverse cohort of Kaiser Permanente Northern and Southern California adult members with incident diagnosed AF between January 1, 2006 and June 30, 2009. Self-reported questionnaires were completed between May 1, 2010 and September 30, 2010, assessing patient socio-demographics, health behaviors, health status, medical history and medication adherence. Medication adherence was assessed using a previously validated 3-item questionnaire. Medication non-adherence was defined as either taking medication(s) as the doctor prescribed 75% of the time or less, or forgetting or choosing to skip one or more medication(s) once per week or more. Electronic health records were used to obtain additional data on medical history. Multivariable logistic regression analyses examined the associations between patient characteristics and self-reported general medication adherence among patients with complete questionnaire data. RESULTS: Among 12,159 patients with complete questionnaire data, 6.3% (n = 771) reported medication non-adherence. Minority race/ethnicity versus non-Hispanic white, not married/with partner versus married/with partner, physical inactivity versus physically active, alcohol use versus no alcohol use, any days of self-reported poor physical health, mental health and/or sleep quality in the past 30 days versus 0 days, memory decline versus no memory decline, inadequate versus adequate health literacy, low-dose aspirin use versus no low-dose aspirin use, and diabetes mellitus were associated with higher adjusted odds of non-adherence, whereas, ages 65-84 years versus < 65 years of age, a Charlson Comorbidity Index score ≥ 3 versus 0, and hypertension were associated with lower adjusted odds of non-adherence. CONCLUSIONS: Several potentially preventable and/or modifiable risk factors related to medication non-adherence and a few non-modifiable risk factors were identified. These risk factors should be considered when assessing medication adherence among patients diagnosed with AF.

Changes in Fall Rates From Before to During the COVID-19 Pandemic: Findings From the Prospective AMBROSIA Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) social distancing policies resulted in reductions in community movement, however, fall rates during this time have not been described. METHODS: This prospective study included adults ≥65 years old participating in the Ambulatory Blood Pressure in Older Adults (AMBROSIA) cohort and who completed ≥1 monthly falls calendar (August 2019-March 2021; n = 250). Months were grouped to correspond to the fall 2020 phased reopening (August-October) and the shelter-in-place policy during the winter 2020 surge (November-January) in Los Angeles, California and compared to the same months, 1 year earlier (ie, before the pandemic). RESULTS: Participants had a mean (standard deviation [SD]) age of 75.2 (6.1) years, 49.6% were White, and 53.2% were women. We obtained 2 795 falls calendars during follow-up. Overall, 110 (44.0%) participants reported a total of 421 falls (rate 15.1 per 100 calendar months). The highest monthly fall rate during the pandemic was 22.9 (95% confidence interval [CI] 16.4-31.1) per 100 calendar-months in August 2020. The lowest fall rate during the pandemic was 8.6 (95% CI 3.5-17.8) per 100 calendar-months in February 2021. During the pandemic, fall rates in August, September, and October 2020 were higher than the previous year (rate ratio 1.8 [95% CI 1.1-2.9]), and fall rates in November and December 2020 and January 2021 were lower than the previous year (rate ratio 0.5 [95% CI 0.4-0.8]). CONCLUSION: As the pandemic continues and older adults resume community mobility after a shelter-in-place period, providers should pay attention to the risk of falls.

Multidrug Resistance of Escherichia coli From Outpatient Uncomplicated Urinary Tract Infections in a Large United States Integrated Healthcare Organization.

Background: Urinary tract infections (UTIs) cause significant disease and economic burden. Uncomplicated UTIs (uUTIs) occur in otherwise healthy individuals without underlying structural abnormalities, with uropathogenic Escherichia coli (UPEC) accounting for 80% of cases. With recent transitions in healthcare toward virtual visits, data on multidrug resistance (MDR) (resistant to ≥3 antibiotic classes) by care setting are needed to inform empiric treatment decision making. Methods: We evaluated UPEC resistance over time by care setting (in-person vs virtual), in adults who received outpatient care for uUTI at Kaiser Permanente Southern California between January 2016 and December 2021. Results: We included 174 185 individuals who had ≥1 UPEC uUTI (233 974 isolates) (92% female, 46% Hispanic, mean age 52 years [standard deviation 20]). Overall, prevalence of UPEC MDR decreased during the study period (13% to 12%) both in virtual and in-person settings (P for trend <.001). Resistance to penicillins overall (29%), coresistance to penicillins and trimethoprim-sulfamethoxazole (TMP-SMX) (12%), and MDR involving the 2 plus ≥1 antibiotic class were common (10%). Resistance to 1, 2, 3, and 4 antibiotic classes was found in 19%, 18%, 8%, and 4% of isolates, respectively; 1% were resistant to ≥5 antibiotic classes, and 50% were resistant to none. Similar resistance patterns were observed over time and by care setting. Conclusions: We observed a slight decrease in both class-specific antimicrobial resistance and MDR of UPEC overall, most commonly involving penicillins and TMP-SMX. Resistance patterns were consistent over time and similar in both in-person and virtual settings. Virtual healthcare may expand access to UTI care.

Ambient temperature and risk of urinary tract infection in California: A time-stratified case-crossover study using electronic health records.

BACKGROUND: In the United States (US), urinary tract infections (UTI) lead to more than 10 million office visits each year. Temperature and season are potentially important risk factors for UTI, particularly in the context of climate change. METHODS: We examined the relationship between ambient temperature and outpatient UTI diagnoses among patients followed from 2015 to 2017 in two California healthcare systems: Kaiser Permanente Southern California (KPSC) and Sutter Health in Northern California. We identified UTI diagnoses in adult patients using diagnostic codes and laboratory records from electronic health records. We abstracted patient age, sex, season of diagnosis, and linked community-level Index of Concentration at the Extremes (ICE-I, a measure of wealth and poverty concentration) based on residential address. Daily county-level average ambient temperature was assembled from the Parameter-elevation Regressions on Independent Slopes Model (PRISM). We implemented distributed lag nonlinear models (DLNM) to assess the association between UTI and lagged daily temperatures. Main analyses were confined to women. In secondary analyses, we stratified by season, healthcare system, and community-level ICE-I. RESULTS: We observed 787,186 UTI cases (89% among women). We observed a threshold association between ambient temperature and UTI among women: an increase in daily temperature from the 5th percentile (6.0 ˚C) to the mean (16.2 ˚C) was associated with a 3.2% (95% CI: 2.4, 3.9%) increase in same-day UTI diagnosis rate, whereas an increase from the mean to 95th percentile was associated with no change in UTI risk (0.0%, 95% CI: -0.7, 0.6%). In secondary analyses, we observed the clearest monotonic increase in the rate of UTI diagnosis with higher temperatures in the fall. Associations did not differ meaningfully by healthcare system or community-level ICE-I. Results were robust to alternate model specifications. DISCUSSION: Increasing temperature was related to higher rate of outpatient UTI, particularly in the shoulder seasons (spring, autumn).

Sociodemographic Inequalities in Urinary Tract Infection in 2 Large California Health Systems.

BACKGROUND: Urinary tract infection (UTI) accounts for a substantial portion of outpatient visits and antibiotic prescriptions in the United States. Few studies have considered sociodemographic factors including low socioeconomic status (SES)-which may increase residential crowding, inappropriate antibiotic prescribing, or comorbidities-as UTI or multidrug-resistant (MDR) UTI risk factors. METHODS: We used 2015-2017 electronic health record data from 2 California health care systems to assess whether 3 sociodemographic factors-use of Medicaid, use of an interpreter, and census tract-level deprivation-were associated with overall UTI or MDR UTI. UTIs resistant to ≥3 antibiotic classes were considered MDR. RESULTS: Analyses included 601 352 UTI cases, 1 303 455 controls, and 424 977 urinary Escherichia coli isolates from Kaiser Permanente Southern California (KPSC) and Sutter Health in Northern California. The MDR prevalence was 10.4% at KPSC and 12.8% at Sutter Health. All 3 sociodemographic factors (ie, use of Medicaid, using an interpreter, and community deprivation) were associated increased risk of MDR UTI. For example, using an interpreter was associated with a 36% (relative risk [RR], 1.36; 95% CI, 1.31 to 1.40) and 28% (RR, 1.28; 95% CI, 1.22 to 1.34) increased risk of MDR UTI at KPSC and Sutter Health, respectively, adjusted for SES and other potential confounding variables. The 3 sociodemographic factors were only weakly associated with UTI overall. CONCLUSIONS: We found low SES and use of an interpreter to be novel risk factors for MDR UTI in the United States.